Description Usage Arguments Value Author(s) Examples
Method for creating a Copula-GARCH filter object.
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spec |
A |
data |
A multivariate data object as ‘matrix’ or ‘data.frame’. |
out.sample |
A positive integer indicating the number of periods before the last to keep for out of sample forecasting. |
filter.control |
Control arguments passed to the filtering routine. |
parallel |
Whether to make use of parallel processing on multicore systems. |
parallel.control |
The parallel control options including the type of package for performing the parallel calculations (‘multicore’ for non-windows O/S and ‘snowfall’ for all O/S), and the number of cores to make use of. |
VAR.fit |
(optional) A previously estimated VAR list returned from calling the
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spd.control |
If the spd transformation was chosen in the spec, the spd.control passes its arguments to the spd fit routine. |
... |
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A cGARCHfilter
object containing details of the Copula-GARCH filter.
Alexios Ghalanos
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## Not run:
data(dji30ret)
Dat = dji30ret[, 1:3, drop = FALSE]
# Copula-Student (non time varying - Max Likelihood Estimation of Rho)
uspec = ugarchspec(mean.model = list(armaOrder = c(1,0)), variance.model = list(model = "sGARCH"),
distribution.model = "std")
spec = cgarchspec(uspec = multispec( replicate(3, uspec) ), VAR = TRUE, VAR.opt = list(lag = 1, lag.max = 4,
lag.criterion = c("AIC", "HQ", "SC", "FPE"), external.regressors = NULL),
dccOrder = c(1,1), distribution.model = list(copula = c("mvt"), method = c("ML"),
time.varying = FALSE, transformation = "parametric"), start.pars = list(), fixed.pars = list())
fit1 = cgarchfit(spec, data = Dat, spd.control = list(lower = 0.1, upper = 0.9, type = "pwm", kernel = "epanech"),
fit.control = list(eval.se = TRUE, trace = TRUE), solver = "solnp")
spec2 = spec
for(i in 1:3){
# This check for non-equal spec which return a list rather than a matrix
if(spec@uspec@type == "equal"){
spec2@uspec@spec[[i]]@optimization.model$fixed.pars = as.list(coef(fit1, "garchpars")[,i])
} else{
spec2@uspec@spec[[i]]@optimization.model$fixed.pars = as.list(coef(fit1, "garchpars")[[i]])
}
}
# "st" is the second-stage parameters
spec2@mspec$optimization.model$fixed.pars = as.list(coef(fit1, "st"))
filt1 = cgarchfilter(spec2, data = Dat, VAR.fit = fit1@mfit$vrmodel)
head(fitted(fit1))
head(fitted(filt1))
## End(Not run)
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